| initialClustering {CIDER} | R Documentation |
Perform batch-specific initial clustering.
initialClustering(
seu,
batch.var = "Batch",
cut.height = 0.4,
nfeatures = 2000,
additional.vars.to.regress = NULL,
dims = seq_len(14),
resolution = 0.6,
downsampling.size = 50,
verbose = FALSE
)
seu |
Seurat S4 object. Required. |
batch.var |
Character. One of the column names of 'seu@meta.data'. It is used to partition the Seurat object into smaller ones. Default: "Batch" |
cut.height |
Numeric. Height used to cut hirerchical trees. Default: 0.4 |
nfeatures |
Number of high variance genes used. Default: 2000 |
additional.vars.to.regress |
Additional variables to regress out. Needs to among column names of 'seu@meta.data'. Default: 'NULL' |
dims |
Number of dimension used for clustering. Passed to Seurat. Default: '1:14' |
resolution |
Resolution for clustering. Passed to Seurat. Default: 0.6 |
downsampling.size |
Numeric. The number of cells representing each group. (Default: 40) |
verbose |
Print the progress bar or not. Default: FALSE |
Seurat S4 object with initial cluster information in 'initial_cluster' of meta.data.